Kubernetes stories
Rising AI costs and weaker oversight are pushing enterprises to demand tighter controls as token use spreads across clouds and in-house models.
Research centres can now keep existing Lustre and GPFS data in place as Fuzzball 4.0 adds Azure support, caching and a registry.
The platform aims to cut idle cloud spend for Kubernetes users, with DevZero saying it can shift workloads live as demand changes without restarts.
Most financial institutions now see unsanctioned AI use as a business risk, with 86% of IT executives warning of weak oversight.
The new features promise to curb Kubernetes cloud spending by spotting stranded capacity that blocks cluster consolidation and auto-scaling.
Users can now route AI and HPC jobs across five clouds and on-premises through one workflow, cutting rebuilds and manual reconfiguration.
Millions of downloads were exposed to silent code execution as a flaw in Hugging Face Transformers let malicious models run on load.
Outages in Kubernetes clusters can now be triaged automatically inside AI tools, cutting the time on-call engineers spend hunting root causes.
Security teams may get a single set of controls for AI agents across clouds as Aviatrix enforces Microsoft policy rules at network level.
The addition gives companies a shared layer for securing and routing AI traffic as agentic systems move into production.
Firms racing to deploy generative AI are exposing themselves to data incidents and compliance gaps, Wallarm says, as oversight lags.
Akamai and NVIDIA are expanding their security partnership to embed Zero Trust controls into AI factory infrastructure.
The move targets vulnerabilities in software used by large firms, as AI makes it easier to find and exploit flaws.
It gives regulated organisations a single platform for private and hybrid clouds, with tighter control over data location and compliance.
The Polish lender expects a 60% drop in virtualisation costs as it shifts hundreds of critical workloads onto Red Hat OpenShift and Hitachi Vantara.
Businesses running GPU-backed AI systems face higher oversight and cost-control risks as emma extends its cloud governance model to production workloads.
Governance and safety controls are now central as businesses push autonomous AI from pilots into production across hybrid cloud systems.
Platform teams can now track Kubernetes and Helm changes in one system as formae broadens its reach into container orchestration and plugins.
Enterprises managing remote sites could cut exposure by combining central container control with outbound-only security.
Rising hardware costs and scarce GPUs are pushing providers towards integrated AI stacks that can cut complexity and TCO, Virtuozzo says.
